IssueSpecter combines coverage analysis with LLM defect detection to generate prioritized, actionable issue reports, achieving 84.6% validity on manually reviewed issues from 13 Python projects and outperforming a coverage-driven baseline.
A deep-learning- based bug priority prediction using rnn-lstm neural networks.e-Informatica Software Engineering Journal, 15(1):29–45
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LLM-Guided Issue Generation from Uncovered Code Segments
IssueSpecter combines coverage analysis with LLM defect detection to generate prioritized, actionable issue reports, achieving 84.6% validity on manually reviewed issues from 13 Python projects and outperforming a coverage-driven baseline.